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QUANTITATIVE RESEARCH METHODS

ENV3QRM

2018

Credit points: 15

Subject outline

Quantitative Research Methods is concerned with the scientific method, the statistical design and analysis of studies in life sciences, and the critical evaluation of scientific literature. Students will learn how scientists discover causal relationships that explain how the natural world operates. Building upon the foundations learnt in STA1CTS Critical Thinking with Statistics, STA1LS Statistics for Life Sciences, or BIO2POS Practice of Science the subject covers the principles of statistical design for surveys, experiments, and observational studies; some new methods for analysing data, including analysis of variance (ANOVA), multiple regression, analysis of covariance (ANCOVA), and some nonparametric methods that are particularly suited to analysing multispecies ecological data; and how to critically evaluate the statistical arguments made in scientific reports and journal articles. Laboratory sessions and assignments will give students the opportunity to apply what they learn using the statistics packages SPSS and PRIMER.

SchoolSchool of Life Sciences

Credit points15

Subject Co-ordinatorWarren Paul

Available to Study Abroad StudentsYes

Subject year levelYear Level 3 - UG

Exchange StudentsYes

Subject particulars

Subject rules

Prerequisites STA1CTS, STA1LS or BIO2POS

Co-requisitesN/A

Incompatible subjects WEM2QRM

Equivalent subjectsN/A

Special conditionsN/A

Readings

Resource Type

Title

Resource Requirement

Author and Year

Publisher

Readings

Statistics explained: An introductory guide for life scientists

Recommended

McKillup, S. (2006)

CAMBRIDGE UNIVERSITY PRESS

Graduate capabilities & intended learning outcomes

01. Design a sample survey, experiment and observational study

Activities:

Guidelines for the design of surveys, observational studies, and experiments are given in the subject notes. A variety of examples and practice problems are given in workshops. Students design a study in Assignment #1.

02. Choose an appropriate analysis for a given research question and data set

Activities:

Guidelines for choosing an appropriate analysis are given in the subject notes. A variety of examples and practice problems are given in workshops and computer labs. Students must choose an appropriate analysis for a given research question and data set in Assignment #2.

A variety of data analysis methods are explained in the subject notes. Examples and practice problems using the output from SPSS and PRIMER are given in workshops and computer labs. Students must choose an appropriate analysis for a given research question and data set and perform that analysis in Assignment #2. They must also interpret the computer output from SPSS and PRIMER and draw conclusions from statistical analyses in the final exam.

04. Communicate statistical analyses in report form

Activities:

Instructions for presenting the results of a statistical analysis in report form, with examples to illustrate the process, are given in Assignment #2.

Guidelines for evaluating statistics reported in scientific literature are given in the subject notes. A variety of examples and practice problems are covered in workshops. Students critically evaluate journal articles in Assignment #1 and #2.

Subject options

Melbourne, 2018, Semester 1, Blended

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorWarren Paul

Class requirements

Computer LaboratoryWeek:
10
-
22
One 3.0 hours computer laboratory per week
on weekdays
during the day
from week 10 to week 22
and delivered via face-to-face.
"Incorporates a 1 hr online workshop with lecturer via Collaborate. Tutor will be in attendance face to face and lecturer will attend via Collaborate."